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Rescuing Relevant Features from Active Aging Surveys: A Data Mining Perspective

Abstract:

Within the psychological currents, several proposals on active aging have been defined, conceptualizing it as a perspective or differentiated way of aging satisfactorily. These proposals generate indicators that assess the level of physical health, psychological well-being and adequate social and spiritual adaptation. The indicators are quantified based on active ageing surveys whose are differs for each ageing proposal and collects different features of active aging such as: health, cognition, activity, affection, fitness, and satisfaction levels. This methodology is focused on rescuing the relevant factors (features) facilitating the interpretation of the data, avoiding the non-required characteristics. The methodology proposes a set of data mining techniques for different types of data that could be present in the forms of active aging, and seeking to make a concrete proposal, the features of an active aging survey are evaluated, determining a subset of features where their weights make them more relevant in data collection, and finally, this methodology is positively evaluated as a model of acceptance by geriatric psychologists.